Field of the Invention
Embodiments of the present invention generally relate to electronic collaboration sessions, and, in particular, to a system and method for recognizing and diagnosing communication link quality problems using real-time textual analysis of user communications.
Description of Related Art
Electronic collaboration sessions may be conducted by use of collaboration systems such as Avaya Aura Conferencing™ or Avaya Scopia™. The electronic collaboration systems may use a client/server architecture. A good quality connection is important in order to provide to users a communication signal (e.g., audio or video media stream) of sufficient quality, in order to prevent artifacts such as video freezes, skipped frames, dropouts, excessive pixellation, choppiness, or other quality of service problems. Therefore, being able to detect and diagnose problems in the quality of the connection for all conference parties is becoming increasingly important. The root cause of audio and/or video problems may be transient, and therefore are difficult to diagnose. Often, by the time a user reports the problem, the root cause may have cleared. Existing troubleshooting methods may require turning on additional debugging or logging tools and waiting for the next occurrence to happen.
Electronic collaboration sessions often include usage of embedded chat functionality, usually provided as part of the collaboration client, in order to communicate with other parties in the collaboration session. The same chat session is often used to communicate with other participants when a user experiences quality of service problems with the voice or video media stream to or from their telecommunication terminal. For example, a video collaboration user on a low bandwidth network connection may receive chat messages from fellow conference participants informing them that their audio and video quality is poor. With existing collaboration applications, an end user is required to perform manual analysis in order to identify the root cause of a quality of service (QoS) problem. The manual analysis may include, for example, manually checking network utilization or manually capturing relevant log files. The end user is not presented with recommendations to improve the quality of their connection, and the collaboration application does not automatically take corrective action to improve the connection.
Furthermore, log files are maintained for only a limited length of time. By the time that a quality of service problem is encountered and reported to an information technology (IT) department for investigation by a technical support team, the log files often have been overwritten or are no longer available.
Although QoS tagging may be provided in collaboration clients to request sufficient resources and proper services from the network, a shortcoming is that QoS tags are not supported in all networks. Another shortcoming is that QoS tagging does not provide, to the end user of a collaboration client, an automatic or suggested action to improve the quality of the connection. Nor do presently available solutions monitor chat conversations among conference participants in order to automatically diagnose and/or QoS problems.
Therefore, a need exists to provide quicker recognition, diagnosis and corrective action of QoS problems, in order to provide a higher quality communication channel, and ultimately improved customer satisfaction.